The increasing incidence and prevalence of prostate cancer in the United States has emphasized the need for methods that enhance early detection of clinically important tumors. The dilemma that remains is that many men harbor prostatic carcinomas that do not become clinically significant in their lifetimes. A better understanding of the early natural history and morphometric characteristics of this disease could provide a basis for more meaningful intervention efforts. Specimens from needle biopsies and radical prostatectomies have provided much information regarding the morphologic characteristics of this disease. However, analysis of such specimens is hampered by the fact that a given patient can be biopsied only a limited number of times and can have a prostatectomy only once. Computer models based on reconstructions of autopsy prostates or radical prostatectomy specimens provide a solution to this problem. This application outlines the rationales and methods to use computer simulations to address a series of translational issues including: 1) optimization of needle biopsy techniques, 2) identification of under-sampled regions of the prostate, 3) definition of clinically significant and insignificant tumors, 4) differences between palpable and non-palpable carcinomas, 5) estimation of tumor volume by needle biopsies, 6) influence of serum PSA on biopsy strategies, 7) influence of age and race on carcinoma characteristics, 8) strategies for successive biopsies and 9)changes in carcinoma characteristics attributable to changes in clinical practice. In addition, immunohistochemical data will be incorporated to address tumor heterogeneity and sampling limitations. The overall goal is to provide more quantitative information about the biomorphometric characteristics of the early stages of prostatic cancer that can be used to improve the clinical management of this increasingly important disease.